ABSTRACT
The repeated occurrence of severe wild†res, which affect various †re-prone ecosystems of the world, has highlighted the need to develop effective tools for monitoring †re-related parameters. Vegetation water content (VWC), which in¤uences the biomass burning processes, is an example of one such parameter [1-3]. The physical de†nitions of VWC vary from water volume per leaf or ground area (equivalent water thickness) to water mass per mass of vegetation [4]. Therefore, VWC could also be used to infer vegetation water stress and to assess drought conditions that linked with †re risk [5]. Decreases in VWC due to the seasonal decrease in available soil moisture can induce severe †res in most ecosystems. VWC is particularly important for determining the behavior of †res
8.1 Introduction .......................................................................................................................... 129 8.2 Data ....................................................................................................................................... 131
8.2.1 Study Area ................................................................................................................ 131 8.2.2 Climate Data ............................................................................................................. 131 8.2.3 Remote Sensing Data ................................................................................................ 133
8.3 Serial Correlation and Time-Series Analysis ....................................................................... 133 8.3.1 Recognizing Serial Correlation ................................................................................ 133 8.3.2 Cross-Correlation Analysis ....................................................................................... 135 8.3.3 Time-Series Analysis: Relating Time Series and Autoregression ............................ 137
8.4 Methodology ......................................................................................................................... 138 8.4.1 Data Smoothing ........................................................................................................ 138 8.4.2 Extracting Seasonal Metrics from Time-Series and Statistical Analysis ................. 139
8.5 Results and Discussion ......................................................................................................... 141 8.5.1 Temporal Analysis of the Seasonal Metrics ............................................................. 141 8.5.2 Regression Analysis Based on Values of Extracted Seasonal Metrics ..................... 141 8.5.3 Time-Series Analysis Techniques ............................................................................ 143
8.6 Conclusions ........................................................................................................................... 143 Acknowledgments .......................................................................................................................... 144 References ...................................................................................................................................... 144
in savanna ecosystems because the herbaceous layer becomes especially ¤ammable during the dry season when the VWC is low [6,7].
